Demographic data have indicated that undernutrition is a common
occurrence for a large proportion of the world's children (Simeon &
Grantham-McGregor, 1990). Evidence relating undernutrition to cognitive
development has been available for at least half a century (Brozek, 1978). In
spite of these facts, interest by behavioral researchers in the role of
nutritional influences on development has been relatively limited, at least as
indicated by available publications on this topic For example, a Psychlit scan
between 1987 and 1992 revealed only 14 references on the topic of nutrition and
cognitive ability, with only seven of these references involving children. In
contrast, a Psychlit scan of studies relating genetics to cognitive ability
yielded 67 studies, 42 of which involved children. It is not clear why
behavioral researchers have tended to neglect the study of nutrition. Perhaps
the fact that the bulk of studies on behavioral development have been done by
researchers from developed countries (Schopflin & Muller-Brettel, 1990) may
have something to do with this relative neglect of links between nutrition and
behavioral development. It is to be hoped that the present Monograph will
go a long way toward remedying this state of benign neglect.

Contributions of the Monograph

There are two major findings that emerge from this data set.
First, there is evidence that early nutritional supplementation can have
long-term developmental consequences for later cognitive performance. If
developmental researchers wish to understand processes influencing variability
in cognitive development in populations other than advantaged children in
Western developed countries, the present pattern of results strongly argues for
the development of models that include nutritional status as a critical
parameter. 1

1

While we tend to think of undernutrition
as a phenomenon found primarily in less developed countries, it is important to
remember that pockets of undernourished populations are also found in Western
developed countries (Karp, in press). Hence, the present findings may also be
relevant for understanding group differences in cognition in developed countries
as well.

The second major finding of this study is that the relation of
nutrition to concurrent and later cognitive performance does not fit a simple
main-effects model. Rather, the relation of nutrition to cognitive performance
is moderated both by the time period during which the nutritional
supplementation was given and by the larger sociodemographic context (social
status, school level) within which subjects resided. For example, children in
the lowest sociodemographic groups benefited more from nutritional
supplementation than did children from higher sociodemographic groups.
Similarly, while there were still nutritional influences when supplementation
was started after 2 years of age, the effect appears to be less powerful. What
these results illustrate is the need to look at nutritional influences as part
of a system of multiple determinants (Wachs, 1993).

The results outlined above also emphasize the need to tailor our
data analysis strategies to recognize the operation of this multidetermined
system. For example, ecological theorists such as Bronfenbrenner (1993) have
contended that traditional analytic approaches for dealing with individual
characteristics or contextual factors, namely, by covarying or partialing them
out, are inappropriate. Covariance or partialing techniques are based on the
assumption that the same developmental processes occur for different individuals
or within different contexts (Bronfenbrenner, 1993). The present findings are a
dramatic demonstration as to why it is important to look for different
developmental processes across different contexts, rather than assuming that the
same main-effect process is operating across contexts. Had Pollitt et al. not
tested for moderating sociodemographic or grade-level influences, they might
well have come to the conclusion that increased nutrition enhances development
for their total sample; this conclusion, although parsimonious, would have been
highly misleading. Given increasing evidence that most behavioral variability
within normal ranges appears to be multidetermined, both at the molecular level
(Plomin, 1990) and at a molar level (Wachs, 1993), the present results offer
further confirmation as to why it is important to consider and not control for
multiple influences on development.

The present project offers not only a set of findings that
emphasize the need to bridge the gap between nutritional and developmental
research but also a model of how a nutritional intervention field study should
be carried out. This study is exemplary in terms of the care taken to identify
potential confounders and, where possible, test for the effect of these
potential confounders. Where it is impossible to test, Pollitt et al. are
explicit in terms of how potential confounders might affect their results. There
are multiple examples that illustrate why this study may be considered as a
model nutritional intervention study. These include testing whether the
supplement was truly a supplement and not just a substitution, looking for
selective migration effects, considering whether attendance at the feeding
station could act as a placebo, and testing for examiner effects. What we have
here is not only a most provocative data set but also a set of guidelines for
how future studies of this type should be designed and implemented.

Unresolved Issues

Methodological Issues

One interesting finding is that nutritional interventions had a
much more dramatic effect on psychometric measures of intelligence and
achievement than on information-processing measures, such as reaction time. A
similar pattern of differential influence is shown for the effects of SES and
schooling. These differences could have important theoretical considerations. It
has been argued that information-processing measures may be more universal (hard
wired) and therefore potentially less responsive to extraneous factors such as
nutrition, schooling, or sociodemographic differences (Kail, 1991). However,
before assuming that this differential reactivity of psychometric versus
information-processing measures reflects differential wiring, we must consider
at least one alternative explanation. As Pollitt et al. show in their Table 13,
the psychometric and achievement measures were more stable than the
information-processing measures. The lower degree of intervention effects for
the information-processing measures may not reflect differential reactivity as
much as the fact that information-processing measures may be less stable.
2 While this study was not designed to test cognitive theory issues
of this type, it is unfortunate that less stable information-processing measures
did result in a loss of potentially interesting information. This may suggest
the need to build in compensatory procedures such as aggregation
(Rushton, Brainerd, & Pressley, 1983) to compensate for potential
stability differences when researchers suspect the possibility of differential
stability for measures from different domains.

2

As a preliminary test of this hypothesis,
I correlated stability coefficients for information-processing measures (Table
13) with the beta coefficients reflecting nutritional treatment effects on these
five measures (Table 19). The resulting correlation, although modest (r
=.26), is in the expected direction, suggesting stronger effect sizes for the
more stable measures.

A second question involves sex differences. While Pollitt et al.
take great care to look for sex differences in the preschool period and in terms
of village demographics, there is a surprising omission in the follow-up data.
Specifically, there is no evidence presented on whether there are sex
differences in either school attendance or school progress. This omission is
particularly surprising given the fact that there are sex differences favoring
males in the results (see Tables 18 and 19) as well as results indicating the
relevance of school factors to subsequent cognitive performance. It could be
argued that, since the sex x treatment interaction was nonsignificant, looking
at sex differences in school functioning is, at best, only a side issue.
However, as elegantly demonstrated by Wahlsten (1990), analyzing for
interactions often results in lower statistical power than analyzing for main
effects. Under these circumstances, if males have higher levels of school
attendance and school progress, it would be useful to consider the potential
role of sex differences in understanding processes underlying
nutrition-cognition relations. This is particularly true if there were also sex
differences in consumption of the supplement as opposed just to
attendance at the feeding station.

Conceptual Issues

In their discussion, Pollitt et al. emphasize the protective
(buffering) effects of supplementation. In fact, what the present results
strongly suggest is double buffering, in the sense that both
supplementation and favorable sociodemographic context can each act as a buffer.
Specifically, if we look within supplementation groups, the lack of SES
differences in the Atole condition clearly shows nutritional buffering, as do
the differences between the Atole and the Fresco groups at the lowest SES level.
However, if we look between conditions, the lack of Atole and Fresco differences
at the upper-SES levels clearly shows that sociodemographic contextual factors
can also act as a buffer for those children who are not nutritionally
supplemented. 3

3

Relations between social class,
nutrition, and cognition suggest the operation of a buffering process, wherein
enhanced nutrition can protect against the risk of low socioeconomic status
while the protective factors that covary with high socioeconomic status can
buffer against the detrimental influence of inadequate nutrition. In contrast,
when we look at the relation between school achievement level, nutrition, and
developmental outcome, buffering does not appear to be operating; children in
the Fresco condition who achieve high grade levels do not necessarily show
superior cognitive performance over Fresco children who do not achieve high
grade levels. Rather, what appears to be operating here is a synergistic
process, wherein maximum performance is achieved with a combination of
nutritional supplementation plus success in school. This illustrates how
different predictor-criterion combinations may be governed by different
underlying processes.

The potential influence of context becomes even more critical when
we look at the explanation offered as to why early nutritional supplementation
influences were maintained and expanded across time. Basically, Pollitt et al.
favor a two-process model, as shown in Figure C1a. First, they propose
that early nutritional differences lead to differences in physical growth;
physical growth differences, in turn, influence how children are subsequently
treated (e.g., smaller children are treated as younger than their chronological
age, whereas larger, more mature-looking children are allowed more autonomy and
independence). It is this differential treatment that is proposed as one
mechanism wherein the effect of early nutritional supplementation is maintained
across time. Support for certain aspects of this model comes from data other
than those described in the present Monograph. For example, in both Egypt
and Kenya, variability in caregiver behaviors toward 18-30-month-old toddlers
was associated primarily with the level of toddler nutritional intake
rather than with the level of caregiver in-take, thus demonstrating that
differences in children's nutrition do relate to how children are treated
(Wachs et al., 1992). Supporting the hypothesis that less adequately nourished
children are treated as if they were younger, in Kenya, and to a lesser extent
in Egypt, inadequately nourished toddlers were carried and held more by
caregivers; toddlers who were carried and held more showed lower levels of
cognitive and behavioral competence.

The second aspect of the proposed model involves higher
nutritional status resulting in increased physical activity. Increased physical
activity in turn results in increased exploratory behavior, which, in turn,
enhances subsequent cognitive development (see Fig. C1a). Again,
support for this model is found in other sources. Previous research has clearly
established linkages between nutrition and activity, between activity and
exploration (Schürch & Scrimshaw, 1991), and between exploration and
cognitive development (Wachs, 1992).

Where the proposed model may be problematic is not so much in its
general outline but rather in terms of not also considering the possibility that
higher-order contextual effects (e.g., culture) may influence how
nutritionally at-risk children are treated. Specifically, in the two-country
study referred to above, the data from Kenya indicate that poorly fed children
not only are carried more but are also responded more to by caregivers;
in contrast, in Egypt, caregivers were less responsive to poorly fed
children (Wachs et al., 1992). These cross-cultural differences between Kenya
and Egypt may reflect differences in level of food intake in the two countries -
Kenyan toddlers had significantly lower food intake than Egyptian toddlers. The
fact that the nutritional level in Guatemala appears to be closer to that of
Kenya than of Egypt suggests that this aspect of the authors' model may be
valid for nutritional-contextual situations in which there is moderate
malnutrition and where cultures support caregivers' attempts to compensate
for inadequate intake by special treatment of the physically smaller child.
However, the model may be less applicable in a context like Egypt, where food is
more available and where poorly fed toddlers may come from families that are
less able to provide for the toddlers' needs in multiple areas of
development, including both nutrition and adequacy of caregiving. The critical
point is that how undernourished children are treated appears to be a function
not only of physical growth but also of cultural differences, suggesting a model
more like that shown in Figure C1b.

FIG. C1. - a, Nutrition model.

FIG. C1. - b, Nutrition-context
model

A similar point can be made in regard to the
nutrition-activity-exploration link. In a number of societies, infants'
physical activity and attempts to explore the environment are likely to be
restricted by their caregivers, either as a function of heavy maternal
work loads or as a function of naturally occurring environmental hazards
(Brazelton, Robey, & Collier, 1969; Kaplan & Dove, 1987; McSwain, 1981;
Super, 1981). In contrast to the model postulated by the authors, in which
higher levels of nutrition result in higher levels of motor behavior, which
result in higher levels of exploration, in some cultures more adequately
nourished children might find their attempts at motor exploration sharply
restricted by their caregivers (see Fig. C1b). As a result, we would not
necessarily expect a developmental advantage in some cultures for more
adequately nourished, physically active children. As the authors themselves
note, the child's capacity to modulate higher activity on the basis of
contextual demands may be more critical than high levels of activity per se.

The alternative model offered in Figure C1b should not be
seen as contradicting the main point of the model offered by Pollitt et al. I
believe that they are essentially correct in suggesting that one path linking
early undernutrition to later deficits in cognitive performance is mediated via
child behaviors and caregiver reactivity. What I am suggesting is that the model
needs to be taken one step further, namely, integrating contextual factors.
Higher-order contextual factors can influence whether caregivers respond in
developmentally facilitative or inhibitory ways toward more adequately nourished
children; these factors can also influence the degree to which caregivers
support or inhibit the child's attempts at activity and exploratory
behaviors.

Implications

The results of the present project are rich, not only in terms of
the actual results, but also in terms of the implications of these results for
future research, theory, and intervention with children at risk.

Research Implications

In their initial review of the study of nutrition-behavior
relations, Pollitt et al. note the possibility that critical nutritional
parameters may involve micronutrients (e.g., vitamins, trace minerals)
rather than energy (kilocalories) or macronutrients (e.g., protein). They also
discuss some of the reasons why more recent nutrition-behavior research has
shifted to experimental field studies rather than correlational studies.
However, if the critical nutrient parameters are micronutrients, this raises the
question of which micronutrients or combinations of micronutrients are
likely to be most salient in influencing developmental variability.
Correlational studies may be initially useful in dealing with this question,
through assessing which micronutrients or micronutrient combinations are most
consistently related to developmental variability. To the extent that
correlational studies can also measure and test the role of nonnutritional
covariates (e.g., morbidity, sociodemographic risk factors, caregiver
behaviors), these types of studies also may be extremely useful in illustrating
the nature of the multidetermined system of influences encountered by the child
who is at nutritional risk. Correlational studies could form the basis for
future intervention-supplementation studies, designed to separate out
correlational from causal relations between nutrition, nutritional covariates,
and development.

A second implication involves the finding that the effect of
nutritional supplementation will be moderated by contextual factors, such as
sociodemographic status and school attendance. I have noted previously in this
Commentary the importance of looking at supplementation effects at different
contextual levels rather than assuming that one supplement feeds all.
Such a strategy illustrates the process by context design, as described by
Bronfenbrenner (1993). However, I would go further and argue that this pattern
of results can also illustrate the importance of looking at individual
differences in reaction to treatment (nutrition or otherwise), within a given
contextual level. In spite of the fact that there are marked individual
differences in response to similar treatment regimens, including both biological
and psychological interventions, the study of these types of individual
differences in reactivity to treatment has been a relatively neglected area in
the behavioral sciences (Wachs & Plomin, 1991). It will be important to
continue looking at the degree to which contexts moderate treatment effects.
However, it will be of equal importance not only to look at mean differences in
reaction to treatment but also to look for variability in response to treatment
within a given context level. For example, for low-SES children who are
nutritionally supplemented in the first 2 years, what are the characteristics
that distinguish those children who benefit more from supplementation from those
who benefit less? This next step leads into what Bronfenbrenner (1993) has
called a person by process by context research strategy.

One obvious drawback of person by process by context research is
sample size, in the sense that, the more subsamples, the fewer subjects at each
subsample, and the lower the power. To some extent, we may be able to compensate
for potentially lower power by increased use of aggregation, more precise
measurement of critical variables, and utilization of statistical procedures
targeted at specific subgroup/individual effects (for a discussion of these
issues, see Wachs & Plomin, 1991). Further, as shown in both the present
Monograph and previously published work by Werner on resilient children
(Werner & Smith, 1982), what we lose in power may be more than made up for
by the richness of data obtained.

Theoretical Implications

As noted earlier, the present results clearly emphasize the
importance of going beyond main-effect approaches when developing models for
understanding the nature of nutrition-development relations. Multidimensional
multidetermined systems approaches seem to offer a much better fit to the data.
Examples of these types of approaches have been developed not only for the study
of nutrition per se (Pollitt, 1988) but also for the more general area of
"determinants" of development (Bronfenbrenner, 1993; Horowitz, 1987;
Wachs, 1992).

The present results also have implications for the question of
sensitive periods in human development. Available reviews suggest that there is
no strong evidence for a critical period in human development and only limited
evidence for sensitive periods (Bornstein, 1989). While the sample size for the
late exposure group was relatively small, the present results at least suggest
the possibility of the continued, although diminishing, salience of nutritional
interventions when started after 2 years of age. These results do not support a
critical periods notion, but they are not inconsistent with theories based on
periods of maximum sensitivity, in the sense that, while earlier may be better,
later may still offer some benefits.

Implications for Intervention

Particularly in less developed countries, theoretically based
research is seen as having less value than research that has practical
implications for individuals' day-to-day lives (Nsamenang, 1992). Pollitt
et al. clearly share this concern, as exemplified by their discussion of public
policy issues. A major policy issue that comes from the present research is the
question of which children should be targeted for nutritional intervention. In
an era of increasingly scarce resources, can we afford to target all children
who are potentially at risk, or should interventions target primarily those
children who are most at risk? If the latter, which children? In the present
project, maximum risk appears to occur for those children who are simultaneously
exposed to inadequate nutrition (no supplementation), low social class, and low
levels of school attainment (the three-way interaction demonstrated) with
Raven's Progressive Matrices).

Clearly, the present results suggest the importance of targeting
low-socioeconomic-status children for nutritional intervention. Providing
nutritional supplementation for these children can be seen as one way of
breaking the naturally occurring covariance between inadequate rearing
environments and inadequate nutrition. However, Pollitt et al. go beyond low SES
and also argue for the importance of considering grade attainment as another
potential risk factor that may call for nutritional intervention. Their argument
is based, in part, on the synergistic interaction between treatment and grade
level as well as on the assumption that, even fat the upper levels of the SES
distribution, there may be only a limited amount of buffering that a poor rural
environment can offer to a child. In contrast, I would argue that the data
presented in this Monograph seem to suggest that supplementation
should be directed primarily toward low-SES children.

There are two reasons for emphasizing SES. First, in contrast to
the authors' argument that there is only so much environmental buffering
that can be offered to children in a poor rural community, the SES buffering
effects for Fresco children show that something positive is being offered to
children, even within this relatively restricted context. Second, the results at
least suggest a diminishing effect of nutritional intervention when started
after 2 years of age. If the strongest effects of nutrition are shown for
children in the first 2 years of life, then the only possible targeting is
social class since at-risk children are not yet enrolled in school. What the
present results could suggest is a two-stage process. In the first stage,
nutritional intervention would be directed primarily toward children in the
lowest social class groups. In the second stage, after children reach school
age, there should be a secondary emphasis on economic aid to families, to
allow supplemented children to remain in school as long as possible.

Conclusions

The present project is a major contribution to the literature, not
only in terms of demonstrating that early nutritional supplementation can have
long-term effects on cognition, but also in terms of illustrating potential
processes whereby nutritional influences interact with the overall context
within which the individual functions. There has been a slowly increasing
emphasis in the literature on biological and contextual linkages. Most of our
current efforts in this direction have involved linkages between genes and
environments (e.g., Plomin & McClearn, in press). The present results
suggest that an equally fruitful path may lie in exploring linkages between
nutrition, context, and the implication of these linkages for developmental
variability.